Fast and reliable fault analysis in complex power systems

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URI: https://hdl.handle.net/11556/1494
ISBN: 0780312171
ISBN: 9780780312173
DOI: 10.1109/ANN.1993.264356
Publication date
1993
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Institute of Electrical and Electronics Engineers Inc.
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Abstract
Neural network approaches to the design of diagnosis systems for electrical networks have to cope with serious problems derived from the large size of such systems, which makes modularity the obvious solution. A modular approach which is based on functional criteria and provides scalability and adaptability to topological changes is presented. The hypotheses generated by the neural system are justified by a competitive system which detects simple or simultaneous disturbances. This approach allows for a parallel, distributed implementation.
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Publisher Copyright: © 1993 IEEE.
Keywords
Fault Diagnosis , Modularity , Neural Networks , Power Systems , Energy Engineering and Power Technology , Control and Optimization , Modeling and Simulation , Artificial Intelligence
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conference output
Citation
Rodríguez , C , Martín , J I , Ruiz , C , Lafuente , A , Rementería , S , Pérez , J & Muguerza , J 1993 , Fast and reliable fault analysis in complex power systems . in Y Tamura , H Suzuki & H Mori (eds) , Proceedings of the 2nd International Forum on Applications of Neural Networks to Power Systems, ANNPS 1993 . , 264356 , Proceedings of the 2nd International Forum on Applications of Neural Networks to Power Systems, ANNPS 1993 , Institute of Electrical and Electronics Engineers Inc. , pp. 14-19 , 2nd International Forum on Applications of Neural Networks to Power Systems, ANNPS 1993 , Yokohama , Japan , 19/04/93 . https://doi.org/10.1109/ANN.1993.264356
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